Real-time fault diagnosis for gas turbine generator systems using extreme learning machine PK Wong, Z Yang, CM Vong, J Zhong Neurocomputing 128, 249-257, 2014 | 181 | 2014 |
Sparse Bayesian extreme learning committee machine for engine simultaneous fault diagnosis PK Wong, J Zhong, Z Yang, CM Vong Neurocomputing 174, 331-343, 2016 | 97 | 2016 |
Fault diagnosis of rotating machinery based on multiple probabilistic classifiers JH Zhong, PK Wong, ZX Yang Mechanical Systems and Signal Processing 108, 99-114, 2018 | 95 | 2018 |
Representational learning for fault diagnosis of wind turbine equipment: A multi-layered extreme learning machines approach ZX Yang, XB Wang, JH Zhong Energies 9 (6), 379, 2016 | 95 | 2016 |
Machine condition monitoring and fault diagnosis based on support vector machine J Zhong, Z Yang, SF Wong 2010 IEEE International Conference on Industrial Engineering and Engineering …, 2010 | 55 | 2010 |
Design and testing of a nonlinear model predictive controller for ride height control of automotive semi-active air suspension systems X Ma, PK Wong, J Zhao, JH Zhong, H Ying, X Xu IEEE Access 6, 63777-63793, 2018 | 54 | 2018 |
A hybrid EEMD-based SampEn and SVD for acoustic signal processing and fault diagnosis ZX Yang, JH Zhong Entropy 18 (4), 112, 2016 | 52 | 2016 |
Multi-fault rapid diagnosis for wind turbine gearbox using sparse Bayesian extreme learning machine JH Zhong, J Zhang, J Liang, H Wang IEEE Access 7, 773-781, 2018 | 40 | 2018 |
Simultaneous-fault diagnosis of gearboxes using probabilistic committee machine JH Zhong, PK Wong, ZX Yang Sensors 16 (2), 185, 2016 | 36 | 2016 |
Gearbox fault diagnosis based on artificial neural network and genetic algorithms Z Yang, WI Hoi, J Zhong Proceedings 2011 International Conference on System Science and Engineering …, 2011 | 34 | 2011 |
A novel multi-segment feature fusion based fault classification approach for rotating machinery J Liang, Y Zhang, JH Zhong, H Yang Mechanical Systems and Signal Processing 122, 19-41, 2019 | 31 | 2019 |
Detection for incipient damages of wind turbine rolling bearing based on VMD-AMCKD method J Zhang, J Zhang, M Zhong, J Zhong, J Zheng, L Yao IEEE Access 7, 67944-67959, 2019 | 30 | 2019 |
Simultaneous‐Fault Diagnosis of Gas Turbine Generator Systems Using a Pairwise‐Coupled Probabilistic Classifier Z Yang, PK Wong, CM Vong, J Zhong, JJY Liang Mathematical problems in engineering 2013 (1), 827128, 2013 | 24 | 2013 |
Correlated EEMD and effective feature extraction for both periodic and irregular faults diagnosis in rotating machinery J Liang, JH Zhong, ZX Yang Energies 10 (10), 1652, 2017 | 15 | 2017 |
A new framework for intelligent simultaneous-fault diagnosis of rotating machinery using pairwise-coupled sparse Bayesian extreme learning committee machine PK Wong, JH Zhong, ZX Yang, CM Vong Proceedings of the Institution of Mechanical Engineers, Part C: Journal of …, 2017 | 14 | 2017 |
An effective fault feature extraction method for gas turbine generator system diagnosis JH Zhong, JJY Liang, ZX Yang, PK Wong, XB Wang Shock and Vibration 2016 (1), 9359426, 2016 | 14 | 2016 |
Research on fault diagnosis method of planetary gearbox based on dynamic simulation and deep transfer learning MM Song, ZC Xiong, JH Zhong, SG Xiao, YH Tang Scientific Reports 12 (1), 17023, 2022 | 8 | 2022 |
Machine learning method with compensation distance technique for gear fault detection Z Yang, J Zhong, SF Wong 2011 9th World Congress on Intelligent Control and Automation, 632-637, 2011 | 7 | 2011 |
Fault diagnosis of rolling bearings under variable conditions based on unsupervised domain adaptation method J Zhong, C Lin, Y Gao, J Zhong, S Zhong Mechanical Systems and Signal Processing 215, 111430, 2024 | 6 | 2024 |
Remaining Useful Life Prediction of Rolling Bearings Based on ECA-CAE and Autoformer J Zhong, H Li, Y Chen, C Huang, S Zhong, H Geng Biomimetics 9 (1), 40, 2024 | 5 | 2024 |